Radiomics and Magnetic Resonance Imaging of Rectal Cancer: From Engineering to Clinical Practice.
Francesca CoppolaValentina GianniniMichela GabelloniJovana PanicArianna DefeudisSilvia Lo MonacoArrigo CattabrigaMaria Adriana CocozzaLuigi Vincenzo PastoreMichela PoliciDamiano CarusoAndrea LaghiDaniele ReggeEmanuele NeriRita GolfieriLorenzo FaggioniPublished in: Diagnostics (Basel, Switzerland) (2021)
While cross-sectional imaging has seen continuous progress and plays an undiscussed pivotal role in the diagnostic management and treatment planning of patients with rectal cancer, a largely unmet need remains for improved staging accuracy, assessment of treatment response and prediction of individual patient outcome. Moreover, the increasing availability of target therapies has called for developing reliable diagnostic tools for identifying potential responders and optimizing overall treatment strategy on a personalized basis. Radiomics has emerged as a promising, still fully evolving research topic, which could harness the power of modern computer technology to generate quantitative information from imaging datasets based on advanced data-driven biomathematical models, potentially providing an added value to conventional imaging for improved patient management. The present study aimed to illustrate the contribution that current radiomics methods applied to magnetic resonance imaging can offer to managing patients with rectal cancer.
Keyphrases
- rectal cancer
- magnetic resonance imaging
- high resolution
- locally advanced
- contrast enhanced
- cross sectional
- clinical practice
- lymph node metastasis
- computed tomography
- case report
- deep learning
- lymph node
- magnetic resonance
- combination therapy
- healthcare
- fluorescence imaging
- social media
- machine learning
- pet ct
- diffusion weighted imaging